Querying the Algorithm List

Function

This API is used to query the algorithm list.

URI

GET /v2/{project_id}/algorithms

**Table 1** Path Parameters
Parameter	Mandatory	Type	Description
project_id	Yes	String	Project ID. For details, see Obtaining a Project ID and Name.

**Table 2** Query Parameters
Parameter	Mandatory	Type	Description
offset	No	Integer	Offset for querying algorithms. The minimum value is 0. For example, if this parameter is set to 1, the query starts from the second one.
limit	No	Integer	Limit of algorithms to be queried. The value ranges from 1 to 50.
sort_by	No	String	Metric for sorting algorithms to be queried. create_time is used by default.
order	No	String	Order of queried algorithms. The default value is desc, indicating that queried algorithms are sorted in descending order. You can also select asc to sort the records in ascending order.
group_by	No	String	Condition for grouping the algorithms to be queried.
searches	No	String	Filter criteria for algorithms to be queried, for example, fuzzy match by the algorithm name.
workspace_id	No	String	Workspace ID

Request Parameters

None

Response Parameters

Status code: 200

**Table 3** Response body parameters
Parameter	Type	Description
total	Integer	Total number of queried algorithms of the current user.
count	Integer	Total number of algorithms that meet the search criteria of the current user.
limit	Integer	Maximum number of queried algorithms of the current user.
offset	Integer	Offset of all algorithm queries of the current user.
sort_by	String	Fields used to sort queried algorithms of the current user.
order	String	Sorting mode of queried algorithms of the current user. The default value is desc, indicating the descending order. You can also set this parameter to asc, indicating the ascending order.
group_by	String	Grouping mode of queried algorithms of the current user.
items	Array of AlgorithmResponse objects	Details about all algorithms that meet the search criteria of the current user.

**Table 4** AlgorithmResponse
Parameter	Type	Description
metadata	metadata object	Algorithm metadata, which describes basic algorithm information.
job_config	job_config object	Algorithm configuration, such as the boot file.
resource_requirements	Array of resource_requirements objects	Algorithm resource constraint. This parameter is optional. After this parameter is set, the console filters available public resource pools when the algorithm is used in training jobs.
advanced_config	advanced_config object	Advanced algorithm policy: auto_search

**Table 5** metadata
Parameter	Type	Description
id	Integer	Algorithm UUID. You do not need to set this parameter when creating an algorithm.
name	String	Algorithm name. The value must contain 1 to 64 characters consisting of only digits, letters, underscores (_), and hyphens (-).
description	String	Description of the algorithm. The value is a string of [0, 256] characters. The default value is NULL.
workspace_id	String	Workspace where a specified algorithm is located. The default value is 0. The value 0 indicates the default workspace.
ai_project	String	AI project to which a specified algorithm belongs. The default value is default-ai-project. The AI project has been brought offline. Ignore it.
user_name	String	Username.
domain_id	String	Domain ID of a user.
source	String	Algorithm source.
api_version	String	Algorithm API version, which identifies the old and new ones.
is_valid	String	Algorithm availability.
state	String	Algorithm state.
tags	Array of Map<String,String> objects	Algorithm tags.
attr_list	Array of strings	Algorithm attribute list.
version_num	Integer	Number of algorithm versions. The default value is 0.
size	Integer	Algorithm size.
create_time	Long	Timestamp when the algorithm is created.
update_time	Long	Timestamp when the algorithm is updated.

**Table 6** job_config
Parameter	Type	Description
code_dir	String	Algorithm code directory, for example, /usr/app/. This parameter must be used together with boot_file.
boot_file	String	Code boot file of the algorithm, which must be stored in the code directory, for example, /usr/app/boot.py. This parameter must be used with code_dir.
command	String	Container startup command of a custom image algorithm.
parameters	Array of Parameter objects	Running parameter of an algorithm.
inputs	Array of inputs objects	Data input of an algorithm.
outputs	Array of outputs objects	Data output of an algorithm.
engine	engine object	Algorithm engine.
code_tree	Array of code_tree objects	Algorithm directory tree
parameters_customization	Boolean	Whether the algorithm allows hyperparameter customization during training job creation.

**Table 7** Parameter
Parameter	Type	Description
name	String	Parameter name.
value	String	Parameter value.
description	String	Parameter description.
constraint	constraint object	Parameter constraint.
i18n_description	i18n_description object	Internationalization description.

**Table 8** constraint
Parameter	Type	Description
type	String	Parameter type.
editable	Boolean	Whether the parameter is editable.
required	Boolean	Whether the parameter is mandatory.
sensitive	Boolean	Whether the parameter is sensitive This function is not implemented currently.
valid_type	String	Valid type.
valid_range	Array of strings	Valid range.

**Table 9** i18n_description
Parameter	Type	Description
language	String	Language.
description	String	Description.

**Table 10** inputs
Parameter	Type	Description
name	String	Name of the data input channel.
description	String	Description of the data input channel.
remote_constraints	Array of remote_constraints objects	Data input constraint.

**Table 11** remote_constraints
Parameter	Type	Description
data_type	String	Data input type, including the data storage location and dataset.
attributes	Array of Map<String,String> objects	Attributes if a dataset is used as the data input. Options: data_format: Data format data_segmentation: Data segmentation dataset_type: Labeling type

**Table 12** outputs
Parameter	Type	Description
name	String	Name of the data output channel.
description	String	Description of the data output channel.

**Table 13** engine
Parameter	Type	Description
engine_id	String	Engine ID selected for an algorithm.
engine_name	String	Engine version name selected for an algorithm. If engine_id is specified, leave this parameter blank.
engine_version	String	Engine version name selected for an algorithm. If engine_id is specified, leave this parameter blank.
image_url	String	Custom image URL selected by an algorithm.

**Table 14** code_tree
Parameter	Type	Description
name	String	Name of the current directory in the algorithm directory tree.
children	Object	Subfiles and subdirectories in the current directory of the algorithm directory tree.

**Table 15** resource_requirements
Parameter	Type	Description
key	String	Resource constraint. The options are as follows: Resource type (flavor_type). The value can be CPU, GPU, or Ascend (tag: hc, hk,fcs_super). Whether to support multi-card training (device_distributed_mode). The value can be multiple or singular. Indicates whether distributed training is supported (host_distributed_mode). The value can be multiple or singular.
value	Array of strings	Value of the resource constraint key.
operator	String	Relationship between keys and values. Currently, only in is supported. For example: flavor_type in [CPU,GPU].

**Table 16** advanced_config
Parameter	Type	Description
auto_search	auto_search object	Hyperparameter search policy.

**Table 17** auto_search
Parameter	Type	Description
skip_search_params	String	Hyperparameter parameters that need to be skipped.
reward_attrs	Array of reward_attrs objects	List of search metrics.
search_params	Array of search_params objects	Search parameters.
algo_configs	Array of algo_configs objects	Search algorithm configurations.

**Table 18** reward_attrs
Parameter	Type	Description
name	String	Metric name.
mode	String	Search direction. max: A larger metric value indicates better performance. min: A smaller metric value indicates better performance.
regex	String	Regular expression of a metric.

**Table 19** search_params
Parameter	Type	Description
name	String	Hyperparameter name.
param_type	String	Parameter type If continuous is specified, the hyperparameter is of the continuous type. When an algorithm is used in a training job, continuous hyperparameters are displayed as text boxes on the console. - discrete: The hyperparameter is of the discrete type. When an algorithm is used for training jobs, discrete hyperparameters are displayed as a drop-down list box on the console.
lower_bound	String	Lower bound of the hyperparameter.
upper_bound	String	Upper bound of the hyperparameter.
discrete_points_num	String	Number of discrete points of a continuous hyperparameter.
discrete_values	String	List of discrete hyperparameter values.

**Table 20** algo_configs
Parameter	Type	Description
name	String	Name of the search algorithm.
params	Array of AutoSearchAlgoConfigParameter objects	Search algorithm parameters.

**Table 21** AutoSearchAlgoConfigParameter
Parameter	Type	Description
key	String	Parameter key.
value	String	Parameter value.
type	String	Parameter type.

Example Requests

The following shows how to query all algorithms in jobs whose names contain TestModelArtsalgorithm and maximum number of algorithms is set to 1.

GET https://endpoint/v2/{project_id}/algorithms?limit=1&searches=name%3ATestModelArtsalgorithm

Example Responses

Status code: 200

{
  "total" : 1,
  "count" : 1,
  "limit" : 1,
  "offset" : 0,
  "sort_by" : "create_time",
  "order" : "desc",
  "group_by" : "",
  "items" : [ {
    "metadata" : {
      "id" : "2e5451fe-913f-4492-821a-2981031382f7",
      "name" : "TestModelArtsalgorithm",
      "description" : "This is a ModelArts algorithm",
      "create_time" : 1636600721742,
      "workspace_id" : "0",
      "ai_project" : "default-ai-project",
      "user_name" : "",
      "domain_id" : "xxxxxxxxxxxxxxxxxxxxxxxxxx",
      "source" : "custom",
      "api_version" : "",
      "is_valid" : true,
      "state" : "",
      "size" : 4791,
      "tags" : null,
      "attr_list" : null,
      "version_num" : 0,
      "update_time" : 0
    },
    "job_config" : {
      "code_dir" : "/algo-test/pytorch/work1/code/",
      "boot_file" : "/algo-test/pytorch/work1/code/test-pytorch.py",
      "command" : "",
      "parameters" : [ {
        "name" : "test-parameter",
        "description" : "",
        "i18n_description" : null,
        "value" : "10",
        "constraint" : {
          "type" : "String",
          "editable" : true,
          "required" : false,
          "sensitive" : false,
          "valid_type" : "None",
          "valid_range" : [ ]
        }
      } ],
      "parameters_customization" : true,
      "inputs" : [ {
        "name" : "data_url",
        "description" : "name to translate"
      } ],
      "outputs" : [ {
        "name" : "train_url",
        "description" : "name to translate"
      } ],
      "engine" : {
        "engine_id" : "pytorch-cp36-1.3.0",
        "engine_name" : "PyTorch",
        "engine_version" : "PyTorch-1.3.0-python3.6"
      },
      "code_tree" : {
        "name" : "code/",
        "children" : [ {
          "name" : "test-pytorch.py"
        } ]
      }
    },
    "resource_requirements" : null,
    "advanced_config" : { }
  } ]
}